The World Wide Web has expanded to provide numerous web services to consumers. The web services may be provided by a web application which uses multiple services and applications to handle a transaction. The applications may be distributed over several machines, making the topology of the machines that provide the service more difficult to track and monitor.
Monitoring a web application helps to provide insight regarding bottle necks in communication, communication failures and other information regarding performance of the services that provide the web application. Most systems being monitored include numerous logs that track system activity and events. The quantity of information provided by these logs is immense, often amounting to terabytes of data generated per day. Because of this excessive quantity of data, log data is not often processed or relied upon by monitoring systems to extract much information.
These large amount of data can be very difficult to investigate manually. In addition, the log format is usually designed for machines, which presents additional challenges for humans to process. Thus, the values from log events are sometimes overlooked and important insights from logs are typically unidentified.
What is needed is an improved system for extracting information from log management systems providing information in a human readable manner.